A communications equipment manufacturing company has a product which is responsible for emitting informative signals. Company wants to build a machine learning model which can help the company to predict the equipment’s signal quality using various parameters.


PROJECT OBJECTIVE: The need is to build a regressor which can use these parameters to determine the signal strength or quality

Import data

Data analysis & visualisation

check null values

Data frame has no null values

From the pairplot it is clear that none of the parameter is good for using a classification model

Parameters 1, 3, 8, 9 have high correlation

Parameters 2, 3 have moderate correlation

Parameters 3 , 9 have moderate correlation

Parameters 6, 7 have high correlation

Hence Parameter 1,2,3,6,7,8,9 can be used to build the model while parameters 4,5,10,11 can be droppped since they exhibit low correlation

PROJECT OBJECTIVE: The need is to build a classifier which can use these parameters to determine the signal strength or quality [as number].

Add classification 1 for Signal strength > 5 meaing good quality and 0 for strength <=5

Part 3: Building GUI